Thanks for validating the pain point..I was also using chatGPT.It's was a pain.We are building something really big to solve the problem of the system developers.Stay tuned.
Hey cjtechie,It's not an another co-pilot.Existing coding co-pilot can only do code generation,code comprehension But not allow you to upload your technical datasheet or crash log etc.Most of the coding agents are SaaS based and SOC2, GDPR and even HIPAA certified. However, these certifications do not guarantee data privacy since they are relatively easy to obtain. Moreover, most SaaS make use of third party providers for different sub-processes (LLMs, embeddings, reranking…), resulting in private data being transferred and stored on numerous servers across the internet.privacy-aware coding SaaS services anonymize sensitive data before sending it to AI. This approach combines the ease of adoption and power of SaaS with data privacy. However, it comes with a single point of failure, which is the anonymization algorithm itself.We solve it by genarting coding datsets and finetuning a small open source coding model on-prem.You can compare the response in a side by side view to gpt-4o model in our platform.
Yes rnavi,I have the same experience as well.The complete system software development can be expedited using AI.Yes, we are doing private beta with a Japanese semiconductor conglomerate.We go with a philoshopy like your data, your model and your cloud.We create instruction dataset from their tech spec and code.Everything on-prem.We have partnered with AMD and Nvidia for on-prem GPU deployment.We help them selecting the right small language coding model and deploying it with securely.
Devin and Cognition are great as co-workers for application software. They're proficient in JavaScript and Python and excel at solving logical problems in software. However, they aren't trained in or familiar with system software, which typically runs on physical devices and requires verification against technical specifications for programming.
We have a team of domain expert who do the vetting of the instruction dataset.We do typical RLHF(Reinforcement learning from human feedback) and connect back to our SFT(supervised finetuning) loop.That's why we name ourself as hardware and human in loop.Humans play an important role in ensuring quality and accuracy of our dataset.
Got it, and how well does it work with more complex documents, like those with a lot of images or intricate tables? I'm curious about how accurately it aligns the content with the source code in those cases.
We use multimodal RAG and tools similar to unstructued.io ,We generate structured output and use LLM again to do the matching with our AST parsed source code.Now matching part is really complex and need manual inspection and validation.
We actually started with go initially. Then we chose to use a different approach to building it (brute force vs inverted indexes) and tested both rust and Go this time. Found rust to be 2x faster for same loop. We knew at this point that we had to choose rust.
Microsoft themselves will be coming up with that sorta integration? I feel the opportunity of this probably is going along the lines of Intercom (support desk) which can be present in chat tool of the client/customer choice itself ?
No sure if they would come up with that in the nearest future. Maybe just adding OpenAI / ChatGPT - it's possible, but I don't think they'e add contextually intelligent bots that would answer queries from your knowledge base.
Right, you should try tapping to old conversation history in these support desk and it would make a good difference on the replies. Didn't see any fine-tuning in the website or docs - do you have plan for these ? I am afraod just langchaining would not make it completely context aware.
thanks for your feedback, again! We're considering to add memory, but in some cases, like in group chat's it can make kind a font noise for the context of your chatbot. So we have to be careful with that.
Sure, we have docs- here's the link: https://ingestai.io/docs and please join our Discor server: https://discord.gg/kMpbueJMtQ where we do our best to assist our users live or even guide throughot the process if needed.
thanks for your comment! Sure, it's even stated on our web-site - our closest releases are: WhatsApp on 2/24, API on 2/25. But we're also woring on adding MS Teams that would be in March 2023.
yes textninja.YoBulk's vision is to automate the first mile data onboarding and cleaning through AI so that Data scientists are free from doing any mundane task of data cleaning.
icelancer,Right now YoBulk is flattening the CSV to JSON with key-value document DB format and storing in MongoDB.You can use GPT3 to create mongo queries to fetch the data.We will be adding APIs soon where you can make a query through GPT3 and fetch the data from Mongo DB.Keep a watch on YoBulk Git repo.
